Smart dosing for microbiome health

Abstract

An application for tracking symptom triggers affecting the microbiome stored on non-transitory computer readable media including an input module for inputting variables from a user in electronic communication with an output variable module, an analysis module for analyzing input variables and output variables, and an output module for presenting results to the user. A method of tracking triggers of symptoms affecting the microbiome in a user, by a user inputting data about nutrition, medication, lifestyle, symptoms due to cancer therapy, pain, and user defined metrics in an application stored on non-transitory computer readable media, performing an analysis on the data, and outputting a result from the data identifying daily activities that effect the user's symptoms and microbiome. A method of adjusting treatment of the microbiome of a patient.

What is claimed is: 
     
         1 . An application for tracking symptom triggers affecting the microbiome stored on non-transitory computer readable media comprising:
 an input module for inputting variables from a user in electronic communication with an output variable module;   an analysis module for analyzing input variables and output variables; and   an output module for presenting results to the user.   
     
     
         2 . The application of  claim 1 , wherein said input module receives data from users in a nutrition question module, medication question module, and lifestyle question module. 
     
     
         3 . The application of  claim 1 , wherein said output variable module includes a symptom question module, and user defined metrics question module. 
     
     
         4 . The application of  claim 1 , wherein said input module receives data from outside devices chosen from the group consisting of general fitness trackers, heartbeat trackers, heart rate trackers, skin temperature trackers, respiratory rate trackers, body posture trackers, eyesight trackers, blood oxygen trackers, glucose level trackers, sleep trackers, body temperature trackers, skin conductance trackers, and combinations thereof. 
     
     
         5 . The application of  claim 1 , wherein said input module receives data from a stool sample analysis of the user's microbiome. 
     
     
         6 . The application of  claim 1 , wherein said input module receives data from outside databases chosen from the group consisting of clinics, electronic medical records (EMRs), pharmaceutical companies, private databases, weather monitoring systems, and CROs. 
     
     
         7 . The application of  claim 1 , wherein said analysis module includes analysis methods of regressions, time series, random forest, classifiers, neural networks, support vector machines, AI/machine learning techniques, miscellaneous classical statistical techniques, and combinations thereof. 
     
     
         8 . The application of  claim 1 , wherein said output module displays strongest trends, key performance indicators, and tracking over time and identifies disease, and microbiome triggers. 
     
     
         9 . The application of  claim 1 , wherein said application is in electronic communication with external databases and healthcare professionals. 
     
     
         10 . The application of  claim 1 , further including an alarm for reminding the user to input data into said input module and said output variable module. 
     
     
         11 . The application of  claim 1 , further in communication with a medical professional who adjusts a dose of a drug chosen from the group consisting of probiotics, prebiotics, supplements, fecal microbiota transplants, and combinations thereof to modulate the user's microbiome. 
     
     
         12 . A method of tracking triggers of symptoms affecting the microbiome in patients, including the steps of:
 a user inputting data about nutrition, medication, lifestyle, symptoms, pain, and user defined metrics in an application stored on non-transitory computer readable media;   performing an analysis on the data; and   outputting a result from the data identifying daily activities that effect the user's symptoms and microbiome.   
     
     
         13 . The method of  claim 12 , wherein said inputting step further includes the step of integrating a user's data from outside devices chosen from the group consisting of general fitness trackers, heartbeat trackers, heart rate trackers, skin temperature trackers, respiratory rate trackers, body posture trackers, eyesight trackers, blood oxygen trackers, glucose level trackers, sleep trackers, body temperature trackers, skin conductance trackers, and combinations thereof. 
     
     
         14 . The method of  claim 12  wherein said inputting step further includes the step of integrating data from outside databases chosen from the group consisting of clinics, electronic medical records (EMRs), pharmaceutical companies, private databases, weather monitoring systems, and CROs. 
     
     
         15 . The method of  claim 12 , wherein said inputting step further includes the step integrating data from a stool sample analysis of the user's microbiome. 
     
     
         16 . The method of  claim 15 , further including the step of predicting triggers based on individuals with similar data to the user. 
     
     
         17 . The method of  claim 12 , wherein said performing an analysis step is further defined as performing an analysis method chosen from the group consisting of regressions, time series, random forest, classifiers, neural networks, support vector machines, AI/machine learning techniques, miscellaneous classical statistical techniques, and combinations thereof. 
     
     
         18 . The method of  claim 12 , wherein said outputting step further includes displaying strongest trends, key performance indicators, and tracking over time. 
     
     
         19 . The method of  claim 12 , further including the step of adjusting a dose or changing the drugs to reduce and/or prevent symptoms. 
     
     
         20 . The method of  claim 19 , wherein the drugs are chosen from the group consisting of probiotics, prebiotics, supplements, fecal microbiota transplants, and combinations thereof. 
     
     
         21 . A method of adjusting treatment of a microbiome of a patient, including the steps of:
 a patient inputting data about nutrition, medication, lifestyle, symptoms, and user defined metrics in an application stored on non-transitory computer readable media;   integrating data from outside devices and outside databases;   performing an analysis on the data;   outputting a result from the data to medical professionals; and   the medical professionals adjusting the treatment of the microbiome of the patient based on the data.   
     
     
         22 . The method of  claim 21 , wherein said adjusting step is further defined as adjusting a dose of a drug chosen from the group consisting of prebiotics, probiotics, supplements, fecal microbiota transplant, and combinations thereof.